Presented herein is a forecast of revenues of Southwest Airlines based on the company’s revenues in the previous five consecutive years. The paper makes reference to the Summer Historical Inventory Data. From the data, the averages are obtained as indicated in the spreadsheet. The averages are then used to convert the data into index. The procedures and the formulas are indicated in the spreadsheet. From the index, a forecast is made for the inventory of the following year. The seasonal patterns are outlined and seasonal indexes estimated. A trend is finally established. The trend is used to analyze the months of the year that needs more or less inventory.
A seasonal pattern can clearly be seen. This makes it possible for estimating the seasonal indexes. The normal time series of the data decreases progressively in January, February and March. The data also decreases in Sept, Oct, Nov, and Dec. Major influxes are in April, May, June, July, and Aug. The trend necessitates that these months with influxes substantially needs more inventory. The four year average, however, exceeds the forecasted amount. Over the four years, there is an upward trend as the index range exceeds the forecast.
The forecast of the next year’s revenue is shown in spreadsheet 2. It’s clearly seen that the revenue has an increasing trend as depicted in the chart below.
These changes can be estimated by straight line since the seasonal changes are more or less constant over time. Therefore, the fluctuation is of the same magnitude in every year. The additive model is therefore appropriate for forecasting. This is shown in the spreadsheet.
This analysis comes with an assumption that the past patterns of change shall continue into the future. Shall the past economic and social factors continue to operate; the same pattern shall be seen in the future. However, any change in these factors is most likely to render the forecast inaccurate. Another problem with this analysis is that it doesn’t attempt to identify what causes the observed patterns. It’s also difficult to tell whether the forces have changed.
In order to better determine the required forecast on the revenue, other factors like consumer price index, the number of employees, the unemployment rate, among others, should be considered. For Southwest Airlines, revenue forecast should be considered together with key factors like unemployment, inflation rate, interest rate, oil and gas prices, and the Producer Price Index. The revenue is directly influenced by these factors. Within this period, the unemployment rate was low; however, the company paid good salary and received several new job applicants. The unemployment data for the last two years (considered herein) is given in the spreadsheet.
Based on the provided inflation data, it can be seen that the inflation during the considered period steadily increases.
Southwest Airlines Team Presentation: Economics. Retrieved 12 Mar. 2012 from http://www.slideshare.net/canouar/southwest-airlines-team-presentation
